Dynamic behaviour of photosynthesis-irradiance curves determined from oxygen production during VARIABLE incubation periods.

 

 

 

Macedo1 M. F., Ferreira2 J. G. & Duarte3 P.

1 Dept. of Environmental Sciences & Engineering, Faculty of Sciences and Technology, New University of Lisbon, 2825 Monte de Caparica, Portugal. E-mail: mfmd@helios.si.fct.unl.pt

2 Dept. of Environmental Sciences & Engineering, Faculty of Sciences and Technology, New University of Lisbon, 2825 Monte de Caparica, Portugal. http://tejo.dcea.fct.unl.pt

joao.imar@mail.telepac.pt

3 Dept. of Sciences & Technology, Fernando Pessoa University, Praça 9 de Abril 349, 4200 Porto, Portugal. E-mail: nop57746@mail.telepac.pt

 

 

Abstract: The production and consumption of oxygen were analysed in phytoplankton populations using a fast biomass-concentration technique. The variation of productivity with irradiance was studied using different incubation periods, from minutes to hours. The influence of the exposure time on the P/I curve parameters was analysed. The results show that dissolved oxygen concentration in the water does not increase linearly with time and that PBmax and Iopt are time-dependent. Exponential and linear expressions were proposed to describe PBmax and Iopt as a function of time. A model was built to investigate the importance of static vs. dynamic simulation in the prediction of phytoplankton production under different light intensities. The results show the importance of using dynamic expressions for the P/I relationship especially in mixed water column.

 

 

Key Words: biomass concentration, phytoplankton productivity, short incubation periods, oxygen method, ecological model.

 

 

Introduction

 

            The photosynthesis-irradiance (P/I) relationship is fundamental to estimates of phytoplankton productivity. Several mathematical models have been proposed for its description (e.g. Steele 1962, Jassby & Platt 1976, Platt et al. 1980, Falkowski & Wirick 1981, Mergard et al. 1984, Eilers & Peeters 1988, Pahl-Wostl & Imboden 1990, Janowitz & Kamykowski 1991). These models can be divided into static and dynamic according to whether they are steady state or time-dependent.

The dependence of photosynthesis on light intensity may be altered by variations recently experienced by the organisms. The major source of these fluctuations is vertical motion (Denman & Gargett 1983), which will not only maintain the phytoplankton population in the mixed layer, but will also have a profound effect on photosynthetic rates.

Short-term (minutes to hours) variation in phytoplankton physiology is a general problem in the measurement and prediction of primary productivity in mixed layers in estuaries. Whereas “in a continental shelf, with a photic zone of 50 m and a vertical diffusion coefficient of about 50 cm2 s-1, a phytoplanktonic cell crosses the photic zone and therefore the full gradient of irradiance in the mixed layer in about 3 days, the same range of irradiance is crossed in 13 minutes, in an estuary with a photic depth of 2 m” (MacIntyre & Geider 1996). In turbid estuaries with shallow waters the photic zone may be less than 0.5m deep, and the phytoplankton may be mixed through most of the photic zone in 3 to 4 minutes (MacIntyre, 1993). Several workers have studied the effect that fluctuations in the light field have on productivity (Marra 1978 a, b, Gallegos & Platt 1985, Yoder & Bishop 1985, Randall & Day 1987, Mallin & Pearl 1992, Franks & Marra 1994, MacIntyre & Geider 1996). There is some evidence that phytoplankton can maintain high rates of photosynthesis during the first minutes after initial exposure to saturating or inhibiting irradiance (Harris & Lott 1973, Harris & Piccinin 1977, Marra 1978 a, b). The major concern is that photoinhibition is a time-dependent process (Kok 1956, Takahashi et al. 1971, Harris & Lott 1973). During mixing, the residence time of phytoplankton in the surface layer, where photoinhibition may occur, is of the same order of magnitude as the time over which phytoplankton can maintain high rates of photosynthesis before photoinhibition becomes prevalent. It is also known that long period incubations (> 2 h) may lead to underestimation of the photosynthetic rates (Lewis et al. 1984, Gallegos & Platt 1985, Pahl-Wostl & Imboden 1990). Therefore the classical way of measuring primary productivity by the light/dark bottle technique, and the use of the results obtained to estimate the P-I curve parameters might lead to overestimation of photoinhibition.

            It is well established that the parameters used in the productivity-light curve change as a result of adaptation at different time scales, suggesting that the dynamic behaviour of the P/I curve parameters should be included in ecological models.

            The problem of determination of short-term processes in phytoplankton physiology is also a problem concerning the methods used to estimate the photosynthetic and respiration rates. The 14C method allows the measurement of carbon fixation even at very low production rates, but artifacts which may arise when using this method (measuring gross or net photosynthesis, use of radioactive material, differential uptake of 14C/12C) are still a matter of controversy (Peterson 1980, ICES 1996). The advantage of the oxygen method is that net primary production (NPP), gross primary production GPP) and respiration (R) may be determined. One of the disadvantages is that heterotrophic respiration is also included in the measurement. More importantly, the sensitivity of this method is usually too low to pick up oxygen changes under short (< 1 h) incubation times. This question may be addressed by concentrating the phytoplankton biomass, in order to reduce the incubation period by increasing the consumption/production of carbon/oxygen (Duarte & Ferreira 1997).

            Experiments using concentrated phytoplankton samples were performed by other authors to measure the photosynthetic and/or respiration rates from natural populations (e.g. Pomeroy & Johannes 1968, Harris & Piccinin 1977). The methodology of concentration found in the literature is very variable, from the Dodson & Thomas (1964) method, through centrifugation (e.g. Iwakuma & Yasuno 1983), to the use of concentrating nets. The first two methods have long time procedures and/or allow only the concentration of small volumes. On the other hand, nets are generally used to quickly filter large volumes of water for taxonomic studies. The main disadvantages of the nets are the potential distortion of species composition due to phytoplankton selectivity, clogging in turbid waters, damage to some organisms (particularly naked flagellates, UNESCO 1978) and inclusion of zooplankton in the sample. In the present work, an alternative phytoplankton concentration net was developed to concentrate large volumes of phytoplankton rapidly without concentrating the zooplankton, clogging or damaging the organisms. This net was tested in a very turbid water column.

Data collected by Marra (1978a, b), Marra & Heinemann (1982) and Cullen & Lewis (1988) have been the basis of several models that relate photosynthesis to fluctuating light intensity (Neale & Marra 1985, Pahl-Wostl & Imboden 1990, Franks & Marra 1994). New data for the relation of time dependence of P/I relationship is presented and a different model for this relation is proposed.

The objectives of the present work are the following:

1)      To develop a technique that allows fast phytoplankton pre-concentration and to explore the potential for short-term photosynthetic measurements using the oxygen method;

2)      To use this technique to study short-term photosynthesis-irradiance (P/I) relationships;

3)      To investigate the influence of the exposure time on the P/I curve parameters;

4)      To develop a primary production model that takes into account the dynamic behaviour of the P/I curve parameters.

 

 

MAterial and Methods

 

            Study area. The Tagus Estuary (Portugal) (Fig. 1) is a large estuarine ecosystem (surface area of 320 km2 and mean volume of 1900´106 m3 (Ferreira & Ramos 1989)). The tidal amplitude ranges from less than 1 m to 4 m during a spring-neap cycle. The Tagus River is the main source of freshwater to the estuary, with a modal discharge of about 400 m3.s-1. This corresponds to an estuary number of less than 1%, indicating that the system should in general be vertically well mixed, which is verified in the field, although the circulation is not laterally homogenous (Carvalho et al. 1997).

 

Fig. 1. (near here)

 

The data were obtained in a channel of the Tagus estuary, with a mean depth of 2.3 m. The salinity ranges from 0 to 32 psu and is strongly influenced by the semi-diurnal and fortnightly tidal cycles. The water is very turbid, with annual values of suspended matter ranging from 45 mg.l-1 to 120 mg.l-1.

            Sampling and treatment. The experiments were performed over a period of six weeks (May-July, 1996) when the biomass of planktonic algae was consistently high, with chlorophyll-a (Chl a) concentrations varying from 8 to 47 mg Chl a m-3. Surface water samples for the determination of physical and chemical parameters and phytoplankton biomass were taken hourly over 3 to 5 hours, depending on the experiment. Temperature, oxygen, salinity and light extinction were measured in situ. The phytoplankton biomass was concentrated using a net built with the aim of rapidly concentrating large volumes of phytoplankton in a turbid water column. This net consisted of 3 filtering cones with different gauze (200 mm, 41 mm and 15 mm) nested inside each other: the first, with 200 mm, did not have a plankton-collecting vessel and was used to restrict the input of detritus and zooplankton (Fig. 2). The water inflow was reduced by the small diameter of the mouth ring and by the non-porous textile cone in front of the net. This modification increased the ratio between the filtering area and the mouth area and reduced clogging.

 

Fig. 2. (near here)

 

            After towing, the net was washed with estuarine water, previously filtered through a 15 mm filter. The plankton was collected from sampling flasks connected to the 41 and 15 mm nets. The filtered water (< 15 mm) was also used as a control sample. All samples were kept in darkness (4 hours) until incubation. The time spent by the phytoplankton cells in the dark was identical  in all the experiments.

            Species determination. Concentrated, non-concentrated and control samples for species determination were preserved with Lugol’s solution. Phytoplankton cells were counted by the Utermöhl technique. Cell abundance data were transformed into relative values of species biomass, through the Taguchi equation (Taguchi, 1976) using cell volumes reported in the literature (Jørgensen et al. 1991).

            Incubation procedures. Samples were incubated in the laboratory using light provided by 1500 W tungsten halogen lamps. Heat produced by the lamps was dissipated using a cold water flow system. Light intensity (0 to 1445 mE m-2 s-1) was measured by a LI-COR underwater cosine quantum sensor and attenuation was achieved by means of grey PVC nets. Preservation of the spectral characteristics was verified by spectral analysis (Fig. 3). Three replicate Winkler flasks (65 ml), volume calibrated to 0.01 ml, were incubated for each light intensity, for periods ranging from 15 to 240 minutes.

 

Fig. 3. (near here)

 

            Chemical analyses. Concentration of oxygen was measured in replicate bottles by titration with the azide modification of the Winkler method (Phillips 1973). A microburette was used to titrate the whole contents of the Winkler bottles (Carritt & Carpenter 1966, Strickland & Parsons 1972). Chlorophyll-a concentration was determined fluorometrically by the method of Yentsch & Menzel (1963) as modified by Holm-Hansen et al. (1965).

            Primary production determination. Productivity and respiration were measured from oxygen differences by the light-dark bottle technique. A photosynthetic quotient of 1.2 and a respiratory quotient of 0.8 were used in the conversion of oxygen to carbon according to Vollenweider (1974) and Geider & Osborne (1989). Three different experiments were performed for primary production determination.

            The purpose of the first experiment (experiment I) was to test whether the rate of oxygen production or respiration was affected by the pre-concentration technique of the phytoplankton biomass. A concentrated phytoplankton sample was diluted with a control sample to obtain different concentrations. All samples were incubated at 100 mE m-2 s-1 for a period of 240 minutes.

            The aim of experiment II was to study the P/I relationships in a natural phytoplankton sample. The incubation was performed with a non-concentrated sample but some phytoplankton was also concentrated for species determination. The samples were incubated for 3 hours at light intensities ranging from 0 to 1280 mE m-2 s-1. Since the choice of different P/I models frequently leads to different estimated parameter values of the P/I curve (Frenette et al., 1993), three different models were used (Table 1). The superscript B denotes that P/I characteristics were calculated per mg chlorophyll-a.

 

Table 1. (near here)

 

            Some of the P/I curve parameters cannot be derived directly from the equations shown in Table 1, therefore some additional calculations were performed. The Iopt (optimal light intensity) and PBmax (maximal production rate) can be directly obtained from Steele’s (1965) equation. The initial slope of the light saturation curve (a) can be determined by

 

   (mgC mgChl a-1 h-1 mE-1 m2 s)                                                (1)

The ratio, PBmax: a , is identical to the parameter Ik defined by Talling (1957) and corresponds to the point at which the linear part of the light-saturation curve intersects the plateau.

The parameters a, b, and PBs directly result from the Platt et al. (1980) model. According to the authors the Iopt parameter can be obtained by

 

   (mE m-2 s-1)                                                                                 (2)

and substituting (2) in the Platt et al. (1980) equation (Table 1) gives the maximum productivity

 

   (mgC mgChl a-1 h-1)                                              (3)

When the photoinhibition parameter (b) tends to zero, PBs tends to PBmax, that is PBmax and PBs coincide if there is no inhibition.

            By differentiating the Eilers & Peeters (1988) model (Table 1) the parametersa, PBmax and Iopt can be expressed as a function of the a, b, and c parameters:

 

                                                                                                                               (4)

 

                                                                                                                        (5)

 

                                                                                                           (6)

and, according to the previous authors, the reverse equations are

 

                                                                                                                      (7)

 

                                                                                                          (8)

 

                                                                                                                               (9)

 

            In the last experiment (experiment III) three replicates of concentrated samples were incubated at different light intensities, from 0 to 1445 mE m-2 s-1 using four incubation periods: 15, 45, 90 and 180 minutes. The influence of exposure time on the P/I curves and parameters was determined. The maximum rate of photosynthesis, PBmax, and the optimal light intensity, Iopt, were described as time-dependent according to the results found in this experiment.

 

            Model development. A productivity function dependent on light intensity and incubation time (P(I,t)) was developed from the Eilers & Peeters model in order to account for the dynamic aspects of the P/I relationships. A simple mathematical model was built using this productivity function, and assuming a respiration rate constant over the time equal to the value determined experimentally. The only biological state variable was phytoplankton and other processes such as nutrient or temperature limitation, were not considered. Primary productivity modelling was carried out by means of static and dynamic formulations. The only difference between these two models is the definition of the productivity function. In the dynamic model the function P(I,t) was used and the parameters changed as a function of the time. In the static model the Eilers & Peeters (1988) P(I) function was used and the parameters remained constant over the simulation period. A time step of 0.1 minutes was used in the simulations. Productivity was expressed as mgO2 mg Chla-1 min-1 and the parameter a was used to calibrate the model.

 

 

Results and discussion

 

A summary of the physical and chemical parameters and chlorophyll-a concentration determined during sampling is presented in Table 2. The chlorophyll-a concentration observed in the field during these experiments was consistently high, which can be related to the sampling season (spring-summer). Data from previous studies (Moita, 1982; Macedo, 1997) reported that phytoplankton biomass in the same area can range from 0.1 to 39 mg Chl.a m-3.

 

Table 2. (near here)

 

            The concentration procedure allowed the concentration of the phytoplankton biomass from a sample with high concentration of suspended particulate matter. It took about 4 hours to collect volumes of 5 to 10 l of concentrated sample. The relative biomass values of the main species found in the concentrated (> 15 mm), non-concentrated (natural population) and control (< 15 mm) samples are presented in Fig. 4. These samples consisted mainly of diatoms. Fragilaria cretonensis was the most abundant species in the concentrated samples, accounting for more than 50% of the total biomass. In the natural (non-concentrated) and control samples F. cretonensis only dominate in the data from experiment I. In the other two experiments the most abundant species were Chaetoceros sp. and Skeletonema costatum, which constituted more than 60% of the natural and control samples. From these experiments it appears that the concentration procedure increases the relative biomass value of the species F. cretonensis.

 

Fig. 4. (near here)

 

It is important to note that the maximal concentration factor (concentrated biomass/non-concentrated biomass) was about 20, in the first experiment, and that a smaller concentration factor, about 3, was found in the other two experiments. This is related to the fact that filtering properties of a net are in part determined by the species composition of the plankton. When chain-forming species (e.g. Skeletonema costatum) or species with spines or setae (e.g. Chaetoceros spp.) are abundant in the natural sample the plankton itself may form a network inside the gauze preventing a high concentration factor (UNESCO, 1978). The number of damaged organisms found was very small, and there was no apparent relation between this number and sample concentration. However it is difficult to ascertain whether a significant number of organisms can be destroyed by the use of this concentration net, because most of the phytoplankters identified were diatoms.

 

In experiment I the effect of the biomass pre-concentration on the rate of oxygen production and respiration was analysed. The results show that the production and consumption of oxygen were linearly correlated with the increase in Chl a concentration (ANOVA p<0.05 and ANOVA p<0.01, respectively) (Fig. 5).

 

Fig. 5. (near here)

 

            It was not possible to measure the respiration rate when the chlorophyll-a concentration was below 45 mg m-3. From these results it appears that concentrating the phytoplankton biomass does not affect specific oxygen production and consumption rates.

            In experiment II natural phytoplankton samples were exposed to different light intensities. The GPP values obtained were fitted to three different mathematical models (Fig. 6) and the P/I parameters were derived after fitting the data to these models using least-squares non-linear regression.

 

Fig. 6 and Table 3 (near here)

 

The equations of Platt et al. (1980) and Eilers & Peeters (1988) have a better fit than Steele’s (1965) equation. The Eilers & Peeters (1988) model was chosen since it is based on the physiology of photosynthesis.

            In experiment III concentrated water samples were exposed to five different light intensities for 15, 45, 90 and 180 minutes. Fig. 7 shows the oxygen evolution over time at the light levels tested. The dissolved oxygen concentration in the water does not increase linearly with time, and at all the light intensities tested the slope is higher for the initial exposure time. It is also noted that for incubation periods longer than 45 minutes the oxygen evolution increases linearly with time, except for the results under highest light intensity.

 

Fig. 7. (near here)

 

            From these data it appears that productivity is not just dependent on light intensity but also dependent on exposure time, as reported by several authors (e.g. Marra 1978, Neale & Marra 1985, Falkowski & LaRoche 1991, Franks & Marra 1994). As the oxygen production does not increase linearly with time, the production rate is not constant, and cannot be estimated as the difference between the final and the initial value of oxygen concentration. To overcome this problem, the gross production rates were calculated for the partial time intervals (0-15; 15-45; 45-90 and 90-180). The respiration rate was determined using 180 minutes of dark incubation. Since there was no data on respiration from shorter incubation periods, a constant respiration rate was assumed. The values obtained were fitted using the Eilers & Peeters’ (1988) equation (Fig. 8 and Table 4).

 

Fig. 8. and Table 4 (near here)

 

            This study was performed during early summer in a temperate zone. The high values of phytoplankton biomass shown in Table 2 reflect a well-known seasonal trend, with high values in spring-summer and low values in winter (Moita 1982, Cabrita & Moita 1995, Macedo, 1997). These biomass values are also a reflection of the considerable primary production rates occurring during this season. In fact, the PBmax values found, for incubation periods longer than 45 minutes (Table 4), fall in the upper range of the representative values, from 0.2 to 17 mg C mg Chl a-1 h-1, proposed by Lalli & Parsons (1993). For shorter incubation periods the PBmax values reported were even higher. Table 5 presents maximal production rates of phytoplankton populations from different sites. From this table it can be seen that the maximum primary production values exhibit a very broad range.

The respiration rate found in this experiment ( 1.8 mg C mg Chl a -1 h-1) ranged from 5% to 19% of the PBmax value, depending on the incubation interval. This relation, R/Pbmax, falls within commonly quoted values, i.e. between 5 and 20 %.

            From Fig. 8 it can be seen that short-time incubation resulted in a saturation curve instead of an inhibition curve. Photoinhibition needs time to develop and become measurable (Kok 1956, Harris & Piccinin 1977, Marra 1978 a, b, Belay 1981, Whitelam & Codd 1983). For short incubations, after the phytoplankton was kept in the dark, all the “photosynthetic factories” (sensu Crill 1977) are in the resting state: When the cells are subsequently exposed to light, the equilibrium between the resting state and the activated state will settle fast (Eilers & Peeters 1988, 1993). This means that in a short incubation period there will be very few transitions from the activated state to the inhibited state, whereas when light intensity remains very high for a long time photoinhibition becomes progressively more important.

            The photosynthetic rate decreases with time for all irradiance levels as can be seen from the plot in Fig. 9. The greatest absolute reduction occurs at the higher light intensities; however, the greatest relative decrease happens at lower irradiances. The results follow a similar pattern to the ones observed experimentally by Marra (1978) and predicted by the DYPHORA model (Pahl-Wostl & Imboden 1990). However in Marra's (1978) data, for irradiance levels lower than or equal to 150 mE m-2 s-1, the curve does not show a decrease with time. Since our data (Fig. 9) have only one light level above this value its not possible to predict if the photosynthetic rate will fallow the same pattern for any given light intensity above 100 mE m-2 s-1.

 

Fig. 9. (near here)

 

In the present study a light inhibition decay time of about 1 to 2 hours was found. This value falls in the range predicted by Pahl-Wostl & Imboden (1990). The critical light intensity for onset of light inhibition must be below 100 mE m-2 s-1, since for all the light intensities tested the exposure time has influence on the production rates.

            From the previous results it seems that all the P/I curve parameters are time-dependent. In some experiments it has been observed that after prolonged illumination with strong light, both PBmax and the initial slope are reduced (Kok 1956, Steeman-Nielsen 1962). Neale & Marra (1985) pointed out that the variation of PBmax  should be considered as the primary source of time-dependence and Franks & Marra (1994) present a non linear time-dependent PBmax. A decrease in the Iopt with time was also observed for light intensities higher than the critical value. Henley (1993) gives examples of experiments conducted by other authors where a reduction in a occurs before any detectable change in PBmax. Such a decrease is not clear from the data presented, since the minimal light intensity used, 100 mE m-2 s-1, is too high for initial slope evaluation. Therefore only the PBmax and Iopt parameters were assumed to be time-dependent. The variation of PBmax and Iopt with exposure time was analysed considering the centre of each time interval (Fig. 10).

 

Fig. 10. (near here)

 

            The parameter Iopt decreases linearly with incubation time. The maximum production rate, PBmax, can be related to time by a negative exponential function, that reduces the PBmax until a constant lower value. This indicates that if phytoplankton is exposed to a critical irradiance for a short period of time, primary productivity may be higher than expected when measured for the same light intensity, after the incubation of phytoplankton for a period of a few hours. However, this relation implies an extremely high PBmax value when the exposure time is zero, which is obviously false. In fact this equation predicts that, for small incubation periods, the PBmax values increase with the decrease of the incubation time. But the experiments were performed until a minimum time of 15 minutes, so prediction of values to lower incubation times would be an extrapolation. According to several authors (e.g. Harris & Piccinin 1977, Pahl-Wostl & Imboden 1990) a rapid increase in productivity, starting from zero, should be expected until the cells reach their full rate of photosynthesis, which must occur after 0.5 to 5 minutes. This rapid increase in the photosynthesis during the first few minutes is probably due to the activation of Rubisco (MacIntyre & Geider 1996). According to these authors the rate at which photosynthesis is induced and reduced, due to increase and decrease of the irradiance, is limited by the kinetics of Rubisco’s activation and deactivation. Therefore, these equations can only be used within the period tested

            A time-dependent model for the P/I relationship was developed from the Eilers & Peeters model. Using equation (7) and (8) and the relation found for the PBmax and Iopt varying with time, the following relation was established:

 

   (mgO2 mgChl a-1 min-1)        (10)

where the production rate is dependent on the light intensity and also on time.

            Using equation (10) for the oxygen production rate a model for the calculation of the dissolved oxygen was built. The model was conceptualised as simply as possible, to investigate solely the importance of dynamic behaviour of oxygen production under different light intensities. The conceptual diagram of this model and the corresponding equations are presented in Fig. 11 and Table 6.

 

Table 6 and Fig. 11 (near here)

 

            The relation between oxygen concentration predicted by this model and the observed data can be seen in Fig. 12. The simulation results indicate that the productivity function, PB(I,t), and the respiration rate used are adequate to describe the observed variation in oxygen concentration during the experiments.

 

Fig. 12. (near here)

 

           

            If the productivity were determined solely from an incubation period of 0 to 180 minutes it would be accepted that the oxygen production increases linearly with time and productivity would be described as a static function, meaning that PBmax and Iopt values should be constant for any given time. In Fig. 13, the results obtained for static and dynamic simulations are compared and evaluated in the light of existing data.

 

Fig. 13. (near here)

 

            As expected, the static model matches the observed values well when the 180 minute curve is used. For incubation periods shorter than 180 minutes the static model underestimates the oxygen concentration. This underestimation is quite significant since the values predicted by the static model for 45 minutes are very close to the values observed at 15 minutes, the same occurring for the 90-minute static curve, which passes near the values determined at 45 minutes of incubation time. When strong vertical turbulence occurs, the time taken by a given phytoplanktonic cell to traverse the full gradient of irradiance, in a 2 m water column, is less than 180 minutes and the static formulation is far from the real data.

                This model gives a dynamic description of photosynthesis and photoinhibition using only three parameters that can be easily deduced from any P/I curve. The PBmax(t) and Iopt(t) equations are represented by simple equations (exponential and linear) which may be fitted to other set of data. Furthermore this model was based on a rational model of the photosynthesis. One of its disadvantages is the assumption of a constant value for a, which is probably not the most realistic approach. Another constraint is the absence of a parameter for the light activation of photosynthesis as described by other authors, e.g. Pahl-Wostl & Imboden (1992) and MacIntyre & Geider (1996). This parameter was not be implemented because the time resolution of our experimental data was not high enough to estimate the activation time.

 

Concluding Remarks

 

 

The main conclusion emerging from the simulations performed is that the dynamic behaviour of the production-light curves is relevant in the simulation of primary productivity, and that this is accentuated when short-term production is determined. Oxygen evolution through time was found to be non-linear and the parameters PBmax and Iopt are time-dependent. Short-term (minutes to hours) variation in phytoplankton physiology is a general problem in the measurement and prediction of primary productivity in the surface mixed layer. When vertical mixing is considered, photoinhibition may be present at higher depths than without mixing, although surface inhibition is weaker than when mixing is absent. This is due to the downward transport of partially or fully inhibited cells (Duarte & Ferreira, 1997). The results show the importance of redesigning the way primary productivity is usually measured by incubating water samples with phytoplankton for several hours at fixed depths.

The concentration procedure used in this study allowed the measurement of production rates by the oxygen method during short incubation periods. This method is easy to implement, less expensive than the radioactive carbon method and allows the calculation of the gross primary production and respiration. The use of this particular design of net has also the advantage of decreasing the errors due to zooplankton respiration. From the results presented in this study it appears that concentration does not affect the production or respiration rates. However the specific diversity and the species composition can be more or less affected by the concentration procedure depending on the species assemblage present. Further research needs to be done in order to improve and test this concentration methodology, but the results obtained are encouraging. This methodology can be very useful for primary production studies, particularly in areas of low productivity, for size-fractionation studies and short-term oxygenic photosynthesis studies, or when radioactive carbon cannot be used.

 

 

Acknowledgements

 

This research was supported by PRAXIS XXI Program (M. Sc. grant BM/534/94), the ECOTEJO project (JNICT PBIC/C/MAR/1293/92) and by SOLVAY - Portugal. We thank F. J. Pina (New University of Lisbon) for helpful discussions and for making laboratory facilities available and P. Mendes for species composition analysis. The authors are also grateful to four anonymous referees for comments and helpful suggestions.

 

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Figures

 

Fig. 1. Cala do Norte of the Tagus Estuary.

 

 

Fig. 2. Towing net used to concentrate phytoplankton.

 

 

 

 


 


Fig. 3. Direct emission spectra of the tungsten halogen lamp and through the PVC net.

 

 


 

 


Fig. 4. Relative percentage of the main taxonomic groups found in the concentrated, non-concentrated and control samples.

 

 

 

 

 


 

 


Fig. 5. Relation between the chlorophyll-a concentration and the oxygen production (a) and consumption (b), obtained from experiment I. Each point represents the mean value of three replicates.

 

 

 

Fig. 6. Photosynthesis versus Irradiance (P/I) curves obtained after fitting the data with the Steele (1965) (a), Platt et al. (1980) (b) and Eilers & Peeters (1988) (c) equations. Each point represents the mean value of three replicates obtained from a non-concentrated sample.

 

 

 

 

 

 

Fig. 7. Variation of the dissolved oxygen concentration during the incubation period at five different light intensities. Each point represents the mean value of three replicates obtained from a concentrated sample.

 

 

Fig. 8. Average productivity calculated from the time intervals 0-15; 15-45; 45-90; 90-180 minutes. The P/I curves were obtained after fitting the data from different incubation times, with the Eilers & Peeters (1988) model. Each point represents the mean value of three replicates obtained from a concentrated sample.

 

 

 

 

 

 


 


Fig. 9. Variation of production rate over time at five light levels. Each point represents the mean value of three replicates obtained from a concentrated sample.

 

 

Fig. 10. Variation of PBmax and Iopt with the exposure time.

 

 

 

 

Fig. 11. Conceptual diagram of the dynamic dissolved oxygen model.

 

 

Fig. 12. Predicted () and observed (l) values of the dissolved oxygen concentration. The slope of the regression line between observed and predicted values is not significantly different from 1 and the y-intercept is not significantly different from 0 (p < 0.05).

 

 

 


 


Fig. 13. Dissolved oxygen values predicted by the dynamic and static models plotted against the observed values.

 

 

 

Tables

 

Table 1. Equations used to calculate the photosynthesis-irradiance (P/I) parameters. Where I is the light intensity, Iopt  is the optimal light intensity, PBmax is the maximal production rate, b is the photoinhibition parameter and a is the initial slope of the light saturation curve.

 

Source

Equation

Type

Steele (1965)

Empirical

Platt et al. (1980)

Empirical

Eilers & Peeters (1988)

Rational

 

 

Table 2. Summary of the physical and chemical parameters and chlorophyll-a concentration determined for the sampling dates.

 

Date

Water temperature

Dissolved oxygen

Salinity

Extinction coefficient (k)

Chlorophyll-a

(1996)

 (ºC)

(mgO2.l-1)

(psu)

(m-1)

(mg.m-3)

May 20

16.5

6.2

0

4.86

7.7

May 20

16

6.8

0

6.8

13.1

May 20

16

7.2

0

6.8

14.3

May 20

16

6.9

0

6.8

13.3

May 20

16

6.9

0

5.7

10.6

June 15

24

nd

nd

nd

46.6

June 19

23

4.5

21

3.4

22.8

June 19

23.5

4.5

16

3.4

14.6

June 19

25

5.2

10.5

4.25

16.9

June 19

25

5.6

8.5

4.86

17.8

June 19

25

6.0

8.0

4.86

19.0

July 2

21.5

8.5

24.5

6.8

21.7

July 2

22

8

19

5.7

23.6

July 2

22.5

8

9.5

6.8

19.9

July 2

23.5

7.8

8

5.7

19.1

July 2

24.5

7.5

14

4.86

23.4

July 2

24

5.8

19

4.25

27.5

nd: not determined

 

Table 3. Parameters of the P/I curve obtained after fitting the data to the Steele (1965), Platt et al. (1980) and Eilers & Peeters (1988) equations: a, the initial slope of the light saturation curve (mgC mgChl a-1 h-1 mE-1 m2 s), PBmax, the maximal production rate (mgC mgChl a-1 h-1), the Iopt , optimal light intensity and Ik light-saturation parameter (mE m-2 s-1).

 

Parameters of the P/I curves

Steele (1965)

Platt et al. (1980)

Eilers & Peeters (1988)

a

0.071

0.118

0.12

PBmax

14.2

12.72

12.89

Iopt

544

433

565

Ik

200

108

103

ANOVA

p > 0.05

p < 0.05

p < 0.05

 

 

 

Table 4. Parameters of the P/I curve, for different incubation periods, obtained after fitting data to the Eilers & Peeters (1988) model: a, the initial slope of the light saturation curve (mgC mgChl a-1 h-1 mE-1 m2 s), PBmax, the maximal production rate (mgC mgChl a-1 h-1), the Iopt , optimal light intensity and Ik light-saturation parameter (mE m-2 s-1).

Incubation period (min)

0 - 15

15 - 45

45 - 90

90 - 180

a

0.259

0.052

0.029

0.03

PBmax

36.3

18.7

13.8

9.65

Iopt

992

942

742

527

Ik

140

336

474

316

 

 

Table 5. Values of maximum production rate, PBmax (mgC mgChla-1 h-1) of phytoplankton populations from different locations.

Authors

Locations

PBmax

 

Lalli & Parsons (1993)

Several

0.2 - 17

Côté & Platt (1983)

Bedford Basin, Nova Scotia

2.04 - 8.37

Savidge (1988)

Strangford Lough, Northern Ireland

0.28 - 20.48

Riegman and Colijn (1991)

North Sea

0.80 - 35.80

Kromkamp and Peene (1995)

Schelde Estuary, Netherlands

0.50 - 18.80

Present study

Tagus Estuary, Portugal

9.56 - 36.30

 

 

Table 6. Equations of the oxygen dissolved model.

 

 

 

 

Phyto- Phytoplankton biomass (mgChl a l-1)

O2 - Dissolved oxygen concentration (mgO2 l-1)

P- Oxygen production (mgO2 l-1 min-1)

R - Respiration (mgO2 l-1 min-1)

Resp. rate. - Experimentally determined respiration rate (mgO2 mgChl a-1 min-1)

PB (I,t) - Production rate (eq. 10)(mgO2 mgChl a-1 min-1)

PBmax - Maximum production rate (mgO2 mgChl a-1 min-1)

Iopt - Optimal light intensity (mE m-2 s-1)

a - Initial slope of the P-I curve (mgO2 mgChl a-1 min-1mE-1 m2 s)

t - time (minutes)